Do local manufacturing firms benefit from transactional linkages with multinational enterprises in China?

This paper examines the linkage effects of foreign direct investment (FDI) on firm-level productivity in Chinese manufacturing. It is found that FDI generates positive vertical linkage effects in Chinese manufacturing at both the national and regional levels, and limited positive horizontal spillovers at the regional level. While OECD firms gain from both vertical and (probably) horizontal linkages, Hong Kong, Macao and Taiwanese firms benefit only from backward linkage effects. In the domestic sector, in which we are most interested, both state-owned enterprises (SOEs) and non-SOEs are hurt by competition from foreign firms in the same industries. While SOEs gain from vertical linkages with foreign firms, non-SOEs are unable to do so. The patterns of productivity spillovers from FDI in Chinese manufacturing seem to be determined by one key factor – the technological capabilities of the firms involved. Important data limitations and policy implications of this research are discussed

ENHANCING RURAL PUBLIC TRANSPORT ACCESSIBILITY THROUGH IMPLEMENTING A SMART SCAN-ON M-TICKETING SOLUTION: : A UNITED KINGDOM CASE STUDY APPROACH WITHIN RURAL DEREGULATED ENVIRONMENTS

Scott Copsey, Sue Walsh, Liam Fassam, Richard Southern, ‘Enhancing Rural Public Transport Accessibility Through Implementing a Smart Scan-on M Ticketing Solution: A United Kingdom Case Study Approach Within Rural Deregulated Environments’, paper presented at the European Transport Conference, Barcelona, Spain, 5-7 October, 2016.The aim of this paper is to demonstrate how two UK Local Authorities (Hertfordshire and Northamptonshire), the two Universities of Hertfordshire and Northampton and public transport providers have worked in partnership to develop a smart scan-on m-ticketing solution, that integrates into a wider ‘smart city’ solution delivering social good through connected value propositions. Based on the initial success of a Hertfordshire pilot, a specific objective of this work is to establish smart integrated multi-operator/modal solutions. This pilot is subsequently being collaboratively expanded upon, through the UK Department for Transport funded ‘Network Northamptonshire Total Transport’ initiative, a transformative project to improve connectivity, integration and accessibility for rural transport networks. This forms part of the recently signed ‘Heart of England’ economic tri-county alliance agreement, which aims to work collaboratively across three local authority regions (Buckinghamshire, Oxfordshire and Northamptonshire), consolidating £3bn of spending. This provides a further future platform for innovative transport solutions being rolled out across wider geographical areas. The initial Hertfordshire demonstrator pilot project explored how a ‘smart’ m-ticketing platform could provide a sustainable financial business model for implementing ticketing solutions for small and medium bus operators within rural Shires, outside of large urban settings. This unique project was the first scan-on bus mobile ticket product used in the UK (outside of London). It offers a partnership model and governance structure for local authorities, commercial operators and other stakeholders with an interest in integrated sustainable transport to take forward, and leads to the possibility of new, socially innovative models for procuring and delivering transport solutions. Initial user reactions have been positive, generating large digital data sets, analysis of which indicates rapid user uptake in comparison to other schemes. This data enables detailed analysis such as precise user geo-spatial distribution, supporting targeted marketing and route-specific promotions to encourage further service uptake. A critical success factor of the project was to target a reduction of on-bus cash handling by five per cent within the first 12 months. This would aid in reducing bus loading times, improve reliability and operator efficiencies. After an initial 16 month operational use, uptake growth in excess of 7 per cent of total revenue has been achieved, on specific routes the transfer to m-ticket has exceeded 12 per cent, with targets of 10 per cent of total cash to mobile conversion predicted by the middle of 2017, likely to be realised. The effectiveness of marketing campaigns, technical development aspects and implementation issues will be reported. These projects have a wider context. Public transport services in rural areas in England are deregulated, and have at present no effective statutory backing or ring-fenced funding. As a result, with reductions in funding to local authorities, funding for non-commercial bus services is being sharply reduced and many authorities are proposing to cease all funding for local bus services (Campaign for Better Transport, 2016). These projects may offer alternative cost-effective ways of providing local transport services in non-metropolitan areas, and thus provide the potential for unique future research opportunities. These include understanding the uptake of smart multi-modal solutions in rural areas to improve accessibility and connectivity through enhanced services for new users and for those with restricted or reduced mobility networks, whilst also offering efficiencies for operators. This research has added importance, because the UK Government is proposing legislation on bus services in England, which would confer significant extra powers on local authorities to intervene in the bus market in various ways. These projects may act as pathfinders for the use of these powers in non-metropolitan areas. Structures supporting a partnership approach involving all those with an interest in public transport are a critical part of improving rural connectivity and accessibility. Through the experience of establishing quality partnership models in Hertfordshire, this paper will go on to detail the subsequent work now underway developing a Social Enterprise model involving local government, universities, operators, health and education services in Northamptonshire, which will form the basis of the transformation of rural integrated sustainable transport delivery.Non peer reviewedSubmitted Versio

A Benchmark for Banks’ Strategy in Online Presence – An Innovative Approach Based on Elements of Search Engine Optimization (SEO) and Machine Learning Techniques

This paper aims to offer a new decision tool to assist banks in evaluating their efficiency of Internet presence and in planning the IT investments towards gaining better Internet popularity. The methodology used in this paper goes beyond the simple website interface analysis and uses web crawling as a source for collecting website performance data and employed web technologies and servers. The paper complements this technical perspective with a proposed scorecard used to assess the efforts of banks in Internet presence that reflects the banks’ commitment to Internet as a distribution channel. An innovative approach based on Machine Learning Techniques, the K-Nearest Neighbor Algorithm, is proposed by the author to estimate the Internet Popularity that a bank is likely to achieve based on its size and efforts in Internet presence.SEO, Internet Website Popularity, banking industry, Machine Learning, K-Nearest Neighbors.

Targeted Employee Retention: Performance-Based and Job-Related Differences in Reported Reasons for Staying

A content model of 12 retention factors is developed in the context of previous theory and research. Coding of open-ended responses from 24,829 employees in the leisure and hospitality industry lends support to the identified framework and reveals that job satisfaction, extrinsic rewards, constituent attachments, organizational commitment, and organizational prestige were the most frequently mentioned reasons for staying. Advancement opportunities and organizational prestige were more common reasons for staying among high performers and non-hourly workers, and extrinsic rewards was more common among low performers and hourly employees, providing support for ease/desirability of movement and psychological contract rationales. The findings highlight the importance of differentiating human resource management practices when the goal is to retain those employees valued most by the organization

A review of portfolio planning: Models and systems

In this chapter, we first provide an overview of a number of portfolio planning models which have been proposed and investigated over the last forty years. We revisit the mean-variance (M-V) model of Markowitz and the construction of the risk-return efficient frontier. A piecewise linear approximation of the problem through a reformulation involving diagonalisation of the quadratic form into a variable separable function is also considered. A few other models, such as, the Mean Absolute Deviation (MAD), the Weighted Goal Programming (WGP) and the Minimax (MM) model which use alternative metrics for risk are also introduced, compared and contrasted. Recently asymmetric measures of risk have gained in importance; we consider a generic representation and a number of alternative symmetric and asymmetric measures of risk which find use in the evaluation of portfolios. There are a number of modelling and computational considerations which have been introduced into practical portfolio planning problems. These include: (a) buy-in thresholds for assets, (b) restriction on the number of assets (cardinality constraints), (c) transaction roundlot restrictions. Practical portfolio models may also include (d) dedication of cashflow streams, and, (e) immunization which involves duration matching and convexity constraints. The modelling issues in respect of these features are discussed. Many of these features lead to discrete restrictions involving zero-one and general integer variables which make the resulting model a quadratic mixed-integer programming model (QMIP). The QMIP is a NP-hard problem; the algorithms and solution methods for this class of problems are also discussed. The issues of preparing the analytic data (financial datamarts) for this family of portfolio planning problems are examined. We finally present computational results which provide some indication of the state-of-the-art in the solution of portfolio optimisation problems

Who are Like-minded: Mining User Interest Similarity in Online Social Networks

In this paper, we mine and learn to predict how similar a pair of users' interests towards videos are, based on demographic (age, gender and location) and social (friendship, interaction and group membership) information of these users. We use the video access patterns of active users as ground truth (a form of benchmark). We adopt tag-based user profiling to establish this ground truth, and justify why it is used instead of video-based methods, or many latent topic models such as LDA and Collaborative Filtering approaches. We then show the effectiveness of the different demographic and social features, and their combinations and derivatives, in predicting user interest similarity, based on different machine-learning methods for combining multiple features. We propose a hybrid tree-encoded linear model for combining the features, and show that it out-performs other linear and treebased models. Our methods can be used to predict user interest similarity when the ground-truth is not available, e.g. for new users, or inactive users whose interests may have changed from old access data, and is useful for video recommendation. Our study is based on a rich dataset from Tencent, a popular service provider of social networks, video services, and various other services in China